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Computational Intelligence Applications for Text and Sentiment Data
Analysis explores the most recent advances in text information
processing and data analysis technologies, specifically focusing on
sentiment analysis from multifaceted data. The book investigates a
wide range of challenges involved in the accurate analysis of
online sentiments, including how to i) identify subjective
information from text, i.e., exclusion of ‘neutral’ or
‘factual’ comments that do not carry sentiment information, ii)
identify sentiment polarity, and iii) domain dependency. Spam and
fake news detection, short abbreviation, sarcasm, word negation,
and a lot of word ambiguity are also explored. Further chapters
look at the difficult process of extracting sentiment from
different multimodal information (audio, video and text), semantic
concepts. In each chapter, the book's authors explore how
computational intelligence (CI) techniques, such as deep learning,
convolutional neural network, fuzzy and rough set, global
optimizers, and hybrid machine learning techniques play an
important role in solving the inherent problems of sentiment
analysis applications.
Sentiment analysis research has been started long back and recently
it is one of the demanding research topics. Research activities on
Sentiment Analysis in natural language texts and other media are
gaining ground with full swing. But, till date, no concise set of
factors has been yet defined that really affects how writers'
sentiment i.e., broadly human sentiment is expressed, perceived,
recognized, processed, and interpreted in natural languages. The
existing reported solutions or the available systems are still far
from perfect or fail to meet the satisfaction level of the end
users. The reasons may be that there are dozens of conceptual rules
that govern sentiment and even there are possibly unlimited clues
that can convey these concepts from realization to practical
implementation. Therefore, the main aim of this book is to provide
a feasible research platform to our ambitious researchers towards
developing the practical solutions that will be indeed beneficial
for our society, business and future researches as well.
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